The effectiveness of interprofessional education: Key findings from a new systematic review
Bibliographic record
Abstract
Over the past decade systematic reviews of interprofessional education (IPE) have provided a more informed understanding of the effects of this type of education. This paper contributes to this literature by reporting an update of a Cochrane systematic review published in this journal ten years ago (Zwarenstein et al., 1999 ). In updating this initial review, our current work involved searches of a number of electronic databases from 1999-2006, as well as reference lists, books, conference proceedings and websites. Like the previous review, only studies which employed randomized controlled trials, controlled-before and-after-studies and interrupted time series studies of IPE, and that reported validated professional practice and health care outcomes, were included. While the first review found no studies which met its inclusion criteria, the updated review located six IPE studies. This paper aims to add to the ongoing development of evidence for IPE. Despite some useful progress being made in relation to strengthening the evidence base for IPE, the paper concludes by stressing that further rigorous mixed method studies of IPE are needed to provide a greater clarity of IPE and its effects on professional practice and patient/client care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.070 | 0.264 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.012 |
| Bibliometrics | 0.019 | 0.019 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.008 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".